IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v615y2023ics0378437123001206.html

New fuzzy multiple regressions for the instantaneous and panel data “The determinants of Poverty in the Countries MENA”

Author

Listed:
  • Belhadj, Besma

Abstract

Habitually, to determine the effect of certain economic and social variables on poverty in MENA, a classical multiple regression with a framework defined a priori verifying several limiting assumptions and easily misused is used. We propose, in this paper, a fuzzy alternative approach to classical multiple regressions with cross-sectional and panel data and explain how the proposed fuzzy methods works in a simple setting. As illustration, we estimates and analyze the effect of the annual GDP growth rate, unemployment rate, inflation rate and the annual population growth rate on poverty in MENA.

Suggested Citation

  • Belhadj, Besma, 2023. "New fuzzy multiple regressions for the instantaneous and panel data “The determinants of Poverty in the Countries MENA”," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 615(C).
    • Handle: RePEc:eee:phsmap:v:615:y:2023:i:c:s0378437123001206
    DOI: 10.1016/j.physa.2023.128565
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437123001206
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
    File URL: https://libkey.io/10.1016/j.physa.2023.128565?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-1054, July.
    2. Besma Belhadj, 2011. "A new fuzzy unidimensional poverty index from an information theory perspective," Empirical Economics, Springer, vol. 40(3), pages 687-704, May.
    3. D'Urso, Pierpaolo & Gastaldi, Tommaso, 2000. "A least-squares approach to fuzzy linear regression analysis," Computational Statistics & Data Analysis, Elsevier, vol. 34(4), pages 427-440, October.
    4. Besma Belhadj & Firas Kaabi, 2020. "New membership function for poverty measure," Metroeconomica, Wiley Blackwell, vol. 71(4), pages 676-688, November.
    5. World Bank, 2018. "Global Financial Development Report 2017/2018," World Bank Publications - Books, The World Bank Group, number 28482, April.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Anis Ochi, 2023. "Inequality and the impact of growth on poverty in sub‐Saharan Africa: A GMM estimator in a dynamic panel threshold model," Regional Science Policy & Practice, Wiley Blackwell, vol. 15(6), pages 1373-1394, August.
    2. Xiaoyu Yin & Xiujian Wei & Muhammad Irfan & Sonia Yasin, 2023. "Revitalizing Organizational Efficiency: Unpacking the Relationship between CEO Turnover, Research and Development, and Pay-Performance Sensitivities in the Financial Sector of Pakistan," Sustainability, MDPI, vol. 15(13), pages 1-15, July.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Belhadj, Besma, 2024. "Fuzzy multiple regressions for Cross-Section and Panel data," Socio-Economic Planning Sciences, Elsevier, vol. 91(C).
    2. Bansal, Ravi & Kiku, Dana & Yaron, Amir, 2016. "Risks for the long run: Estimation with time aggregation," Journal of Monetary Economics, Elsevier, vol. 82(C), pages 52-69.
    3. Kutuk, Yasin, 2022. "Inequality convergence: A world-systems theory approach," Structural Change and Economic Dynamics, Elsevier, vol. 63(C), pages 150-165.
    4. Smoluk, H. J. & Neveu, Raymond P., 2002. "Consumption and asset prices: An analysis across income groups," Review of Financial Economics, Elsevier, vol. 11(1), pages 47-62.
    5. Alessandra Canepa & Fawaz Khaled, 2018. "Housing, Housing Finance and Credit Risk," IJFS, MDPI, vol. 6(2), pages 1-23, May.
    6. Isaiah Andrews & Anna Mikusheva, 2016. "Conditional Inference With a Functional Nuisance Parameter," Econometrica, Econometric Society, vol. 84, pages 1571-1612, July.
    7. Jessica M. Mc Lay & Roy Lay-Yee & Barry J. Milne & Peter Davis, 2015. "Regression-Style Models for Parameter Estimation in Dynamic Microsimulation: An Empirical Performance Assessment," International Journal of Microsimulation, International Microsimulation Association, vol. 8(2), pages 83-127.
    8. Jarle Aarstad & Olav Andreas Kvitastein & Stig-Erik Jakobsen, 2019. "What Drives Enterprise Product Innovation? Assessing How Regional, National, And International Inter-Firm Collaboration Complement Or Substitute For R&D Investments," International Journal of Innovation Management (ijim), World Scientific Publishing Co. Pte. Ltd., vol. 23(05), pages 1-25, June.
    9. Alex Cukierman & Anton Muscatelli, 2001. "Do Central Banks have Precautionary Demands for Expansions and for Price Stability?," Working Papers 2002_4, Business School - Economics, University of Glasgow, revised Mar 2002.
    10. Li, Yuming, 1998. "Expected stock returns, risk premiums and volatilities of economic factors1," Journal of Empirical Finance, Elsevier, vol. 5(2), pages 69-97, June.
    11. Pastor, Lubos & Stambaugh, Robert F., 2003. "Liquidity Risk and Expected Stock Returns," Journal of Political Economy, University of Chicago Press, vol. 111(3), pages 642-685, June.
    12. Carlos Medel, 2017. "Forecasting Chilean inflation with the hybrid new keynesian Phillips curve: globalisation, combination, and accuracy," Journal Econom a Chilena (The Chilean Economy), Central Bank of Chile, vol. 20(3), pages 004-050, December.
    13. Lily Liu, 2017. "Estimating Loss Given Default from CDS under Weak Identification," Supervisory Research and Analysis Working Papers RPA 17-1, Federal Reserve Bank of Boston.
    14. Aysit Tansel & Nil Demet Güngör, 2016. "Gender Effects of Education on Economic Development in Turkey," World Scientific Book Chapters, in: Nadereh Chamlou & Massoud Karshenas (ed.), Women, Work and Welfare in the Middle East and North Africa The Role of Socio-demographics, Entrepreneurship and Public Policies, chapter 3, pages 57-86, World Scientific Publishing Co. Pte. Ltd..
    15. Jin, Hyun Joung & Kim, Jang-Chul & Su, Qing, 2025. "Economic freedom and market resilience: Safeguarding liquidity in times of crisis," Journal of Multinational Financial Management, Elsevier, vol. 79(C).
    16. Heng, Dyna, 2011. "Capital flows and real exchange rate: does financial development matter?," MPRA Paper 48553, University Library of Munich, Germany, revised May 2012.
    17. Castelló-Climent, Amparo & Mukhopadhyay, Abhiroop, 2013. "Mass education or a minority well educated elite in the process of growth: The case of India," Journal of Development Economics, Elsevier, vol. 105(C), pages 303-320.
    18. Kampelmann, Stephan & Rycx, François, 2012. "The impact of educational mismatch on firm productivity: Evidence from linked panel data," Economics of Education Review, Elsevier, vol. 31(6), pages 918-931.
    19. Baharumshah, Ahmad Zubaidi & Slesman, Ly & Wohar, Mark E., 2016. "Inflation, inflation uncertainty, and economic growth in emerging and developing countries: Panel data evidence," Economic Systems, Elsevier, vol. 40(4), pages 638-657.
    20. Guglielmo Maria Caporale & Anamaria Diana Sova & Robert Sova, 2024. "The Covid‐19 pandemic and European trade flows: Evidence from a dynamic panel model," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 29(3), pages 2563-2580, July.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C60 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - General
    • I32 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Measurement and Analysis of Poverty

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:phsmap:v:615:y:2023:i:c:s0378437123001206. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.